Social based aggregation of related media content

ABSTRACT

Systems and methods for media aggregation are disclosed herein. The system includes a media system that can transform user generated media items into at least one aggregated media item. A synchronization component can synchronize media items with respect to time. Synchronized media items can be analyzed and transformed into an aggregated media item for storage and/or display. In addition, the aggregated media item is capable of being manipulated to create an enhanced and customizable viewing and/or listening experience. Accordingly, media item aggregation can be accomplished.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.13/361,776, filed on Jan. 30, 2012, entitled “SOCIAL-BASED AGGREGATIONOF RELATED MEDIA CONTENT,” the entirety of which is incorporated hereinby reference.

TECHNICAL FIELD

This disclosure relates to aggregation of related media content, andmore particularly to controllable aggregation of a plurality of users'respective media content for a particular event.

BACKGROUND

The proliferation, advancement, and affordability of image capturingdevices such as smart phones, digital cameras, and other electronicdevices has made media capturing easier and more available to thegeneral public than ever before. Sharing of videos captured byindividuals attending a particular sporting event, wedding, musicconcert or birthday party, etc. by way of a social media website hasbecome commonplace. Videos of a same event are often uploaded bydisparate people that attended the event. For example, querying anexisting media sharing website for a video of an event, such as “5^(th)grade concert New York,” can result in dozens if not hundreds of videofiles of that event. Respective videos of a common event are oftenrecorded at different angles of view, different distance from the targetof the video, different locations with respect to acoustic and/orlighting quality, different device capabilities (e.g., image capturequality, encoding, audio sensors, processing capabilities, etc.), andother differing aspects that manifest in the recorded video.

SUMMARY

The following presents a simplified summary of the specification inorder to provide a basic understanding of some aspects of thespecification. This summary is not an extensive overview of thespecification. It is intended to neither identify key or criticalelements of the specification nor delineate the scope of any particularimplementations of the specification, or any scope of the claims. Itspurpose is to present some concepts of the specification in a simplifiedform as a prelude to the more detailed description that is presented inthis disclosure.

In an implementation, an identification component receives a media itemfrom a user and associates the media item with media items of the sameevent which were created by at least one different source (e.g., adifferent user). The media item can be associated via user input orautomatically through analysis of video content and a relationshipbetween video sources (e.g., a relationship between two or more users).A synchronization component synchronizes the media items (e.g.,synchronization based on a time correlation). Optionally, an analyzercomponent can be employed to analyze and rank the media items or aplurality of intervals (e.g., a frame, or group of frames) of the mediaitems, based on at least one criterion, e.g., video quality. One or moreintervals can form a segment. In another example, an editing componentcan be employed to receive user input and apply user input to customizeanalysis. An aggregation component then aggregates the synchronized andranked segments of media items for aggregated playback.

In another example, a set of video files is associated based on commoncontent. The video files are then synchronized based on time andanalyzed and ranked based on video quality, audio quality, videocharacteristics (e.g., color, light, and/or motion), audiocharacteristics (e.g., audio levels, noise, and/or pitch), compositionand/or user preference (e.g., a plurality of intervals are ranked). Inone example, the media files are analyzed frame by frame, ranked andthen grouped into segments. The segments are aggregated according torank into a new composite media item by an aggregation component. Theaggregated files can be viewed by a user and/or a plurality of users.The plurality of users can be granted access according to user accessrules. For example, user access rules may be set according to whoauthored a media item or a relationship between users. The aggregatedmedia file can seamlessly change between video files and/or audio files.

The following description and the drawings set forth certainillustrative aspects of the specification. These aspects are indicative,however, of but a few of the various ways in which the principles of thespecification may be employed. Other advantages and novel features ofthe specification will become apparent from the following detaileddescription of the specification when considered in conjunction with thedrawings.

BRIEF DESCRIPTION OF THE DRAWINGS

Numerous aspects, implementations, and advantages of the presentinvention will be apparent upon consideration of the following detaileddescription, taken in conjunction with the accompanying drawings, inwhich like reference characters refer to like parts throughout, and inwhich:

FIG. 1 illustrates a high-level functional block diagram of an examplemedia system in accordance with various aspects of this disclosure;

FIG. 2 illustrates an exemplary synchronization of media items inaccordance with various aspects of this disclosure;

FIG. 3 illustrates a high-level functional block diagram of an examplemedia system including an editing component in accordance with variousaspects of this disclosure;

FIG. 4 illustrates a high-level functional block diagram of an examplemedia system including an output component in accordance with variousaspects of this disclosure;

FIG. 5 illustrates an example diagram of a real world event inaccordance with various aspects of this disclosure;

FIG. 6 illustrates an example diagram of a set of captured media itemsin accordance with various aspects of this disclosure;

FIG. 7 illustrates an example methodology for aggregating media items inaccordance with various aspects of this disclosure;

FIG. 8 illustrates an example methodology for aggregating media itemsaccording to user input in accordance with various aspects of thisdisclosure;

FIG. 9 illustrates an example methodology for aggregating media itemsand displaying media items in panoramic format in accordance withvarious aspects of this disclosure;

FIG. 10 illustrates an example schematic block diagram of a computingenvironment in accordance various aspects of this disclosure; and

FIG. 11 illustrates an example block diagram of a computer operable toexecute various aspects of this disclosure.

DETAILED DESCRIPTION

Various aspects or features of this disclosure are described withreference to the drawings, wherein like reference numerals are used torefer to like elements throughout. In this specification, numerousspecific details are set forth in order to provide a thoroughunderstanding of this disclosure. It should be understood, however, thatcertain aspects of disclosure may be practiced without these specificdetails, or with other methods, components, materials, etc. In otherinstances, well-known structures and devices are shown in block diagramform to facilitate describing this disclosure.

Systems and methods disclosed herein relate to aggregation of mediaitems uploaded by a plurality of users. In one implementation, a mediasystem is employed to aggregate a plurality of videos. A plurality ofusers capture and upload multiple video files of an event such as awedding, a school play, a children's sporting event, an entertainmentevent, a party, a school event, and/or other private events, (employingany of a variety of suitable video capture devices, e.g., video cameras,smart phones, tablets, e-readers, personal computers, and smart phones)to a data store (e.g., a server in communication with a computerreadable storage medium).

Respective video files are collected by a collaborative environment forpublication so that the user and others (e.g., friends, family membersand other contacts) can access the video. The video files can becollected in any suitable manner (e.g., directly from a recordingdevice, using a personal computer, smart phone, or tablet) and stored inone or more servers. Each server includes various components stored in acomputer readable medium that perform respective functions such asanalyzing the videos, acquiring features of the videos (e.g.,determining the event that was recorded, a time of recording, an authorof video, the type of recording device, a format of the video, alocation of the event, individuals within the video, angle of recording,quality of the video, quality of associated audio, lighting, etc.),classifying the videos, associating the videos with similar videos(e.g., videos of the same event), and providing for aggregating subsetsof the videos. In one exemplary implementation, a user can opt-out ofhaving particular information collected and/or shared with the server.

In one implementation, a component stored in a server determines thatcertain videos are related based on, for example, metadata or byanalyses of the content of the videos. Metadata can include informationrelated to time of capture, location of capture, and/or tags, forexample. In one aspect, time and location information can be providedvia a global positioning system (GPS) or communication network accesspoints (e.g., internet connection access points). Time and locationinformation associated with respective videos can determine arelationship between the respective videos. Tags can be associated witheach video by users or by automatic tagging techniques. Tagging refersto associating a key word, set of words or phrase with the video,wherein the associated key word(s) or phrases are referred to as atag(s). For example, a user can tag a captured video with “Christmasconcert” “New York” “December, 2011” “5^(th) grade”. In oneimplementation, respective user input can be employed to associate anuploaded video with other video(s) of a common event. In anotherexemplary non-limiting implementation, an event entity, such as an eventpage, is defined and videos are associated with the event entity asopposed to directly associated with each other.

In one embodiment, a subset of related videos is subsequentlysynchronized. The synchronization can be performed according to time, orother suitable synchronization metrics. For example, a time line can bedetermined through audio recognition, pattern recognition, captured time(e.g., time stamp), a clock, or a combination thereof. The videos can beanalyzed in connection with various metrics or criteria (e.g., videoquality, audio quality, angle of recording, level of noise, lighting,and frequency of appearance of certain people or objects). For example,with respect to a set of videos associated with a particular schoolconcert, a user may wish to focus on a particular child (e.g., theparent's own child) in the concert and input such criteria. In oneimplementation, a user's input can be stored for later use. Analyses ofthe set of videos or portions thereof can determine (e.g., using facialrecognition) image size and frequency of appearance of the child's facein respective videos of the set. In one implementation, videos (orintervals thereof) within the set are ordered and/or ranked based on oneor more desired criterion (e.g., image size, and frequency of appearanceof the child). In one aspect, a set of users can access the set ofvideos (e.g., edit, watch and/or review). The set of users cancollaborate to edit the aggregated video and/or create multipleaggregated videos based on the set (and/or a subset of the set) ofrelated videos. The set of users, or a subset thereof, can be grantedaccess to perform actions on the set of media items according to useraccess rules. For example, user access rules may be defined according towho authored a media item. User access rules include defining who canview a plurality of media items, edit a plurality of media items, reviewthe plurality of media items, and publish a new media item.

Respective subsets of video segments can be aggregated to generate oneor more new media items that emphasize desired aspects of the analyzedvideos. The aggregated new media item(s) can display respective videostransformed into single composite video (e.g., stitch video for seamlessplayback). With reference to the above school concert example, theaggregated new media item can include seamless switching between aplurality of videos as a function of respective rank.

In an implementation, sound associated with each video can be combinedor selectively chosen for playback. For example, analysis of audioinformation can determine highest quality audio associated withrespective videos. Then, the selected audio can be played based on rankand/or combined with other audio. Audio of one video can be combinedwith an image portion of another video. Respective aggregated new mediaitems can contain surround sound qualities through aggregation ofmultiple audio files.

Media items can be synchronized, analyzed, and aggregated according toaudio quality, video quality, audio characteristics (e.g., focusing onbass, treble, amplitude, pitch, dB level, etc.), video features, or thelike.

Referring now to FIG. 1, there is illustrated a non-limiting exemplaryimplementation of a media system 100 that provides media aggregation inaccordance with various aspects of this disclosure. The system 100provides for aggregation of media items that are captured, uploadedand/or viewed by a plurality of users in a collaborative environment.The system 100 receives media item(s) 114 (e.g., audio and or videoinformation) that are respectively captured and uploaded to the system100 by a set of users. Respective users can capture and upload the mediaitem(s) 114 via any suitable electronic device, such as for example acamera, smart phone, video camera, tablet computer, laptop computer,personal computer and cell phone, via a communication framework (e.g.,the Internet or cellular network). The media item(s) 114 can be providedto an identification component 110 at concurrent, overlapping ordisparate times. In one example, users upload respective media itemsyears apart.

In FIG. 1, the system 100 includes a computer processing unit 104capable of executing various components stored in a computer readablememory 106, such as an identification component 110, a synchronizationcomponent 120, an analyzer component 130, and an aggregation component140. Memory 106 can store media item(s) 114. Identification component110 associates a subset of the media items that pertain to a commonevent (e.g., a concert, a play, a sporting event, an entertainmentevent, a party, a school event, and/or other private events).Identification component 110 can identify the common event throughextrinsic information or analyses associated with respective media items(e.g., image or audio recognition, metadata comparison, user input(e.g., tagging information), authors, location, time and/or content). Inone example, metadata is generated automatically, such as via a globalpositioning system (GPS), or wireless location triangulation. Inaddition, time and location information can be generated bycommunication framework access points or routing information. Forexample, users can upload respective media items via a wireless routerin a school auditorium and media identification component 110 canassociate the respective media items with that location.

Synchronization component 120 automatically synchronizes associated setsand/or subsets of media items. The associated media items can besynchronized as a function of common characteristics (e.g., soundrecognition, motion recognition, pattern recognition, time stamps,etc.). In one aspect, the media information synchronization is performedwith respect to time. Synchronization component 120 can identify acommon time line by comparing like characteristics in the set and/orsubset of media item(s), metadata such as time stamps, or a combinationthereof.

In one example, motion and/or pattern recognition identifies commonmovements of a pattern in a plurality of video files to synchronize aset of media items. Further, synchronization component 120 can matchvisual features in the media items and find temporal alignmentparameters that maximize geometrical constraints such as for examplehomography matching or Fundamental matrix constraint. In another aspect,each frame of a video can be synchronized by overlapping frames of atleast one other video. Alternatively or additionally, key frames can beselected for synchronization. In another example, synchronization canrely at least in part on correlation of media items' respective audio.For example, matching of audio signals can be utilized to create acommon time line.

In another example, audio recognition is applied to audio of therespective media items to identify common characteristics. The commoncharacteristics can be used to create a common timeline among the set orsubset of media items.

Analyzer component 130 analyzes a set of temporally synchronized mediaitems based on any of a variety of suitable metrics (e.g., videoquality, audio quality, presence of a subject in video, composition ofvideo, angle of video and/or audio) that facilitate identifying segmentsof respective media items with desirable attributes. In oneimplementation, analyzer component 130 groups media items associatedwith a common event into one or more subsets of media items. Respectivesubsets of media items can be grouped based on any of a variety ofsuitable metrics.

In one non-limiting exemplary implementation, analyzer component 130partitions respective media items into portions (e.g., frames and/orintervals). An interval can be a number of frames or a time interval(e.g., one second interval). A rank is given to each portion. Theportions can be grouped into a set of segments (e.g., ten secondsegments). In one embodiment, intervals are grouped into segments as afunction of rank (e.g., audio quality, video quality, and/or othermetric).

In one example, analyzer component 130 ranks media items and groups themedia items into respective subsets based on the rank (e.g., ranking andgrouping as a function of video quality). Video quality may be evaluatedvia video quality assessment (VQA) algorithms and techniques. Suchtechniques can include peak signal to noise ratio (PSNR), structuralSIMilatary (SSIM), Multi-scale SSIM (MS-SSIM), Speed SSIM, and/or VisualSignal to Noise Ratio (VSNR).

In another example, analyzer component 130 can determine video qualitybased on subjective user analysis. In one example, users can associate aquality with a video. The quality may be a level on a subjective scalesuch as number of stars or a number out of ten. In another example,video quality can subjectively be determined based on multiple userinput. Multiple user input may be an average ranking, a cumulativeranking (e.g., users may increase or decrease a quality by one), and/ora combination of the above. In another implementation, video quality canbe assessed automatically based on objective metrics (e.g., resolution,lighting quality, smoothness, frame transitions, color, authorreputation).

Audio component quality associated with respective media items can vary.Audio component quality variation may be a result of several factorssuch as for example electronic equipment used in capturing audio,compression and decompression, orientation and distance from sourceaudio, and/or background noise. In one aspect, audio component qualitycan be analyzed via audio quality evaluation techniques. For example,audio quality evaluation can be based on perceptual based audio qualitymethods (e.g., perceptual evaluation of audio quality (PEAQ), perceptualevaluation of speech quality (PESQ)), non-perceptual based audio qualitymethods (e.g., total harmonic distortion (THD), signal to noise ratio(SNR)), noise ratio (NR), spectral distortion (e.g., Bark spectraldistortion), and/or comparison of parameters (e.g. loudness, amplitudemodulation, adaption, masking parameters, linear distortion, bandwidth,and modular difference). In another example, at least one ofpsychoacoustic evaluation models or cognitive evaluation models can beemployed to evaluate audio component quality.

In another example, analyzer component 130 can determine audio qualitybased on subjective user analysis. For example, one or more users canassociate a quality to an audio aspect of a media item.

In an implementation, analyzer component 130 can employ patternrecognition techniques and/or systems to determine a rank associatedwith respective portions of a set of media items 114. The analyzercomponent 130 can determine a frequency rate of a pattern (e.g., howoften a pattern appears) in each portion and/or segment of the pluralityof media items 114. Analyzer component 130 can associate a higher rankwith portions of the plurality of media items 114 with higher frequencyrates.

In one example, analyzer component 130 can employ face/objectrecognition techniques on the portions to determine differentpeople/objects. As another aspect, analyzer component 130 can employclothing identification (e.g. by color) to boost people recognitionrates. As another example, analyzer component 130 can employcomposition/place detection techniques to cluster video frames by colormoments (where 0 order moment would be the color histogram).

Further, analyzer component 130 can associate a rank with each portionand/or segment. A rank can be determined as a function of at least oneanalyzed metric. For example, analyzer component 130 can rank eachportion and/or segment based on video composition (e.g., a higher rankis associated with media items of a desired composition). In anotheraspect, a plurality of metrics can be applied to determine rank. Forexample, analyzer component 130 can rank each media item based on afunction of video composition, video quality and audio quality.

In one aspect, analyzer component 130 divides media items into a set ofintervals. Respective temporally corresponding intervals of media itemscan be ranked. Sets of intervals related to the same source media itemcan be ranked as a function of an appropriate metric (e.g., videoquality, audio quality, presence of a subject in video, composition ofvideo, angle of video and/or audio) and grouped into segments. System100 can record a rank and associate portion and/or segment in memory(e.g., as an array) for aggregation.

In one non-limiting exemplary implementation, analyzer component 130 canautomatically and dynamically assign a rank to portions and/or groupportions into segments with use of a dynamic Bayesian network such as aHidden Markov Model (HMM) using a Viterbi algorithm. For example, a HMMcan be configured for a face/person emphasis, scene/compositionemphasis, and/or video/audio quality emphasis (e.g., resolution,sharpness, contrast, color saturation, audio noise) such that divisioninto segments and ranking according to a metric occur simultaneously orsubstantially simultaneously. In an example, a HMM pairwise term dependson audio level (to prefer transition in quiet times) and on motionmagnitude (to prefer transition during less action). In another aspect,local terms can depend on presence of some people/objects, videoquality, audio quality, composition and the like.

In an implementation, analyzer component 130 can identify media contentuploaded by members of a social circle or social network. The analyzercomponent 130 can make such identification using any suitable means suchas for example, image recognition and/or accessing, as authorized,social networks, user published relationships, network connections,metadata, email or phone contacts, etc. Ranking of subsets of mediacontent can be a function of a social relationship between respectiveusers and/or association of sources of respective media content. Forexample, a group of users with an association in a social network canupload media content. The media content can be analyzed to identify eachof users of the group of user's specific criteria and ranking analyzercomponent 130 can automatically rank portions of the media items basedon combined user affinity towards objects.

Accordingly, the analyzer component can identify subsets of mediacontent that are respectively generated by people that have arelationship or association (e.g., family, friends, co-workers, membersof an organization, etc.), and who may desire to generate a compositemedia work that aggregates media content created by members of theirsocial circle or network.

Aggregation component 140 transforms a set of media items into a newaggregated media item. Further, aggregation component 140 aggregates(e.g., stitches) a set of media items into a single seamless media item.In one aspect, aggregation component 140 stitches media items and/orsegments of media items based on an associated rank to create a newmedia item. In another aspect, aggregated component 140 associates atleast one media item with every moment of a common time line (e.g., acommon timeline created by synchronization component 120) such thatcontent from at least one media item is associated with each moment ofplayback.

In another implementation, given a HMM result, transitions can beremoved to avoid a short segment. For example, a threshold time can bedetermined (e.g., 10 seconds). The given HMM result can yield portionsor intervals grouped into segments whose associated segment lengths aresmaller than the threshold. Segments with associated lengths small thanthe threshold can be eliminated such that the prior segment orsubsequent segment can be assigned to the eliminated segments time slot.As another example, transitions between segments can be implemented bysmooth transitions such as fade-out/in.

Turning to FIG. 2, with reference to FIG. 1, a graphical depiction 200of media items synchronized on a common timeline 202 is provided. InFIG. 2, four different user captured video items (media items A, B, C,and D (205, 215, 220, 225)) are shown. The media items pertain to acommon event. Each respective video item can be taken over same,different, or overlapping time periods. Each respective video item maybe taken using different types of devices, e.g., different consumerelectronic devices. For example, video items may be taken using a mobilephone by one user, a point-and-shoot digital camera by another user, anda different portable device by another user. While only four differentmedia items are shown for illustrative purposes, a different numbermedia items could be depicted instead.

In one example, identification component 110 creates a set of mediaitems A, B, C, and D (205, 215, 220, 225) from a plurality of mediaitems 114. The set of media items are associated to a common event(e.g., concert, play and/or sporting event).

Synchronization component 120 can identify the common feature(s) 210 ofmedia items A, B and C (205, 215, 220). In one aspect, the commonfeature(s) may be recognized via image recognition, motion recognition,and/or audio recognition. Additional feature(s) can be identifiedbetween at least two media items of the set of media items A-D. In oneaspect, synchronization component 120 can synchronize media items one ormore times. In one example, media items A, B, C, and D (205, 215, 220,225) may be synchronized according to identified key frames, frame byframe, randomly, and/or periodically.

In another implementation, synchronization component 120 defines anaudio timeline by identifying common audio features of media items A, B,C, and D (205, 215, 220, 225). The common audio timeline may be used tosynchronized audio and video playback and/or as a basis for audioaggregation.

Synchronization component 120 identifies or defines a common timeline202. The common timeline 202 can have associated start and end times foreach media item A, B, C, and D (205, 215, 220, 225). FIG. 2 depictsmedia items with the following time associations: media item A (205)begins at a time T0 and lasts until T6; media item B (215) begins attime T2 and lasts until T7; media item C (220) begins at T1 and lastsuntil T5; and media item D (225) begins at T3 and lasts until T4.

In an aspect, analyzer component 130 associates a rank with respectiveportions of the set of media items A, B, C, and D (205, 215, 220, 225).

Analyzer component 130 can temporally rank respective portions as afunction of a desired metric. For example, analyzer component 130 canrank respective portions of media item A (205) and C (220) associatedwith the period T1 to T2. In addition, analyzer component can rankrespective to portions of media items A (205), B (215) and C (220)associated with period T2 to T3. In an implementation, analyzercomponent can store ranks of respective clips in an array.

Aggregation component 140 can aggregate the set of media items A, B, C,and D (205, 215, 220, 225) and/or respective portions and/or segments ofmedia items, into one or more new aggregated media items as a functionof rank. In one example, a media item and/or segment of a media itemwith a highest rank is selected for display for each respective momenton an associated timeline. In another example, highest ranked segmentsare stitched to create a seamless new aggregated media item. Stitchingcan refer to associating one portion and/or segment with a time intervalof the common time line. The associated portions and/or segments can betransitioned for a seamless playback. The seamless aggregate media itemis an ideal or substantially ideal media item with respect to desiredmetrics.

Referring to FIG. 3, there is illustrated a non-limiting exemplaryimplementation of media system 300 that provides media item aggregationaccording to an aspect of this disclosure. In use, a plurality of usersuploads media items 306 to system 300. Media system 300 includes acomputer processing unit 304 capable of executing various componentsstored in a computer readable medium (e.g., memory 306), such as anidentification component 310, a synchronization component 320, ananalyzer 330, an aggregation component 340, and an editing component350. In one embodiment, memory 106 also stores the media item(s) 314.Identification component 310 collects media items and associates mediaitems of common events. Synchronization component 320 synchronizes mediaitems with respect to time. Analyzer component 330 analyzes aspects ofmedia item portions and ranks respective portions of media items.Aggregation component 340 aggregates the analyzed and synchronized mediaitems into at least one new aggregated media item.

In one implementation, editing component 350 modifies analysis andranking by analyzer component 330 and aggregation by aggregationcomponent 340. In one example, user input 360 is received by editingcomponent 350. Analyzer component 330 can place greater importance on ametric as a function of user input 360. In one example, editingcomponent 350 receives user input 360 and ranks media items or segmentsof media items based entirely on user input. In certain implementations,basing ranking entirely on user input can eliminate and/or substantiallyreduce the need for analyzing media items.

In one example, editing component 350 can receive user input 360 from aset of users. For example, a user of the set of users can input one ormore criteria and a different user of the set of users can input one ormore additional criteria. Input from the set of users can place greaterimportance on a metric for analyzing. In another aspect, input from aset of users can associate a rank with media items (and/or portions ofmedia items).

In another implementation, editing component 350 can apply rightsassociated with respective users to facilitate collecting user input.For example, rights associated with a user may be watch, edit, preview,and/or review past changes. In a collaborative environment, respectiveusers' rights can dictate which users can edit, watch and/or reviewmedia items before, during or after an aggregation.

In one implementation, aggregation component 340 stitches media itemsand/or segments of media items to create a customized new media item asa function of user input 360 and/or appropriate metrics.

Turning now to FIG. 4, there is illustrated a non-limiting exemplaryimplementation of a media system 400 that provides media aggregation,according to an aspect of this disclosure. Media system 400 includes acomputer processing unit 404 capable of executing various componentsstored in a computer readable medium (e.g., memory 406), such as anidentification component 402, a synchronization component 410, ananalyzer 430, an aggregation component 440, a editing component 450, andan output component 454. In one embodiment, memory 106 also stores themedia item(s) 414. Identification component 402 receives media items 404and associate media items 404 into sets of media items pertaining torespective common events. Synchronization component 410 synchronizesmedia items with respect to time. Analyzer component 430 analyzes andranks media or portions thereof according to at least one metric.Aggregation component 440 transforms a set of media items to at leastone new media item.

In one implementation, editing component 450 modifies analysis andranking by analyzer component 430 and aggregation by aggregationcomponent 440. In one example, user input 448 is received by editingcomponent 450. Analyzer component 430 can place greater importance on ametric as a function of user input 460. In one example, editingcomponent 450 receives input and ranks media items or segments of mediaitems based entirely on user input. In certain implementations, basingranking entirely on user input can eliminate and/or substantially reducethe need for analyzing media items.

Output component 454 can publish the at least one new media item. In oneaspect publishing the new media item can include saving the new mediaitem in memory 406 and/or presenting (e.g., streaming, broadcasting,transmitting, downloading, and/or displaying) the published new mediaitems using a server(s) and/or a client device(s). In one aspect, the atleast one new media items cannot be edited. However in oneimplementation, a published new media item can be saved in memory 406for further editing in a collaborative environment.

Referring now to FIG. 5 with reference to FIG. 4, there is illustrated adiagram of an event in accordance with various aspects of thisdisclosure. In FIG. 5, the event is a school concert where there is astage 502 and a student performer 504 on the stage 502. A plurality ofelectronic devices (510, 512, 514, 516) captures media items of theevent. Each media item captured by the electronic devices (510, 512,514, 516) has an associated field of view (520, 522, 524, 526,respectively). In one example, media items captured by the plurality ofelectronic devices (510, 512, 514, 516) vary in audio quality, videoquality, angle, and capture content (e.g., focus on different areas ofstage 502). In use, each electronic capture device may be owned by adifferent user (e.g., a different parent of students in the schoolconcert) and each user may upload the media item captured by his/herdevice to a user generated content (UCG) hosting site. In oneimplementation, an output component 454 provides for panning betweenfields of view of respective media items. For example, output component454 may allow for output media information to display the field of view520 and can pan (e.g., according to user input received by editingcomponent 450) to view 526 by transitioning to view 522, 524 and then526.

Referring now to FIG. 6 with reference to FIG. 4, there is illustrated adiagram of captured media item frames in accordance with various aspectsof this disclosure. In FIG. 6, there are various outputs of frames offour distinct media items. In one example, media item frame 610represents a frame of a first media item with a complete view of aperson, media item frame 620 represents a frame of a second media itemwith an obscured view of a person, media item frame 630 represents aframe of a third media item with a partial view of a person, and mediaitem frame 640 represents a frame of a forth media item without a viewof a person (e.g., capturing a different area of an event). In use, eachmedia item can be captured from a device that may be owned by adifferent user (e.g., a different parent of students in a schoolconcert) and each user may upload the media item captured by his/herdevice to a user generated content (UCG) hosting site. In oneimplementation, analyzer component 430 can automatically analyze andrank a media item frame (e.g., frame 610) as superior based on one ormore metrics. In another aspect, editing component 450 can receive userinput 448 to rank media item frames 610, 620, 630, and 640. While onlyfour different media item frames are shown for illustrative purposes, adifferent number media items could be depicted instead. While media itemframes are shown for illustrative purposes, media item segments orintervals could be depicted instead.

Referring now to FIGS. 7-9, there are illustrated methodologies and/orflow diagrams in accordance with the disclosed subject matter. Forsimplicity of explanation, the methodologies are depicted and describedas a series of acts. However, acts in accordance with this disclosurecan occur in various orders and/or concurrently, and with other acts notpresented and described herein. Furthermore, not all illustrated actsmay be required to implement the methodologies in accordance with thedisclosed subject matter. In addition, those skilled in the art willunderstand and appreciate that the methodologies could alternatively berepresented as a series of interrelated states via a state diagram orevents. Additionally, it should be further appreciated that themethodologies disclosed hereinafter and throughout this specificationare capable of being stored on an article of manufacture to facilitatetransporting and transferring such methodologies to computers. The termarticle of manufacture, as used herein, is intended to encompass acomputer program accessible from any computer readable device or storagemedium.

With reference to FIG. 7, there is illustrated a methodology 700 foraggregating media information, according to an aspect of thisdisclosure. As an example, various media applications, such as, but notlimited to, media capturing systems, social networking systems, and UGCsystems can use methodology 700. Specifically, methodology 700transforms multiple media items into a single new aggregated media item.

An input component can receive a set of media items (e.g., by an inputcomponent) at 702. For example, a plurality of users can upload mediaitems from a plurality of client devices (e.g., one or more smartphones, personal computers, tablet computers, and/or PDAs) to aserver(s) and/or social video network(s) through a communicationframework (e.g., internet, cellular network, satellite and/or ethernet)to an input component. In another aspect, the set of media items can bestored in a compute readable medium (e.g., volatile and/or nonvolatilememory).

At 704, a media system can associate media items. For example, the setof media items can be associated with a second set of media itemspertaining to a common event (e.g., by an identification component).

Turning to 706, media items are synchronized (e.g., by a synchronizationcomponent). In one aspect, media items are synchronized with respect totime. Synchronization may be based on identifiable aspects of mediainformation such as common audio or video characteristics. In oneexample, synchronization is based, at least in part, on metadata such astime stamps.

At 708, media items are analyzed (e.g., by an analyzing component).Analyzing media items may include analyzing respective portionsaccording to appropriate metrics such as audio/video quality, presenceof a subject in video, composition of video, angle of video and/ordivision of media items into appropriate segments.

At 710, media item portions can be ranked and grouped into media itemsegments (e.g., by an analyzing component) and an appropriate segmentcan be found). For example, an analyzer component can find theappropriate media item segment (e.g., find the media item segment whichis to be aggregated). Ranking can comprise associating a unique rankwith each portion and/or segment as a function of an analyzed metric(s)and/or a feature(s). In one aspect, temporally respective media itemsegments are ranked relative to each other.

Turning to 712, media items are transformed into one or more newaggregated media item (e.g., by an aggregation component). The newaggregated media item can comprise multiple media items respectiveportions and/or segments stitched together to create a seamless andoptimal (or nearly optimal) media item. In another aspect, transitionsbetween media item segments are applied to smooth playback.

Referring to FIG. 8 there illustrated is a methodology 800 for userspecific media item aggregation, according to an aspect of thisdisclosure. As an example, methodology 800 can be utilized in variousweb applications, media capturing systems, media displaying systems,computing devices, cellular phones, etc. Specifically, methodology 800enables utilization of user defined criteria to provide for aggregatemedia files of a common event which most interest a user.

Initially, media items can be captured or can be contained within amemory (e.g., memory 306). At 802, a user can define criteria foraggregation (e.g., via input collected by an editing component).Criteria for aggregation can be related to identifiable characteristicsof media items such as frequency of a visual pattern in frames (e.g., aface, object, and/or other pattern), video quality, audio quality, imagecharacteristics, video characteristics (motion, brightness, color),and/or sound characteristics (e.g., bass, treble, noise), for example.

At 804, a set of media items is synchronized with respect to time (e.g.,by a synchronization component). At 806, media items and/or portions ofmedia items can be analyzed according to the user defined criteria(e.g., by an analyzing component utilizing user input). For example,media items can be divided into portions (e.g., frames and/or intervals)and the portions can be analyzed.

At 808, the set of media item portions can be ranked according to theuser defined criteria (e.g., by an analyzing component). In anotheraspect, the media item portions of the set of media item portions aregrouped into segments (e.g., by an analyzing component). The appropriatemedia item segment for a time period can be found or determined based onanalyzed metrics. For example, a user may select video quality as themost important attribute for ranking. Thus, media item portions withhigher associated video quality will have a higher rank. In anotherexample, a set of users can provide respective input to access a set ofmedia items (e.g., view, edit, preview and/or review an aggregationproject). In one aspect, the set of users can save changes made to a setof media items and/or associated ranking. The saved changes areavailable for future editing of the set of media items and/or associatedranking.

At 810 sets of media item portions and/or segments are transformed intoone or more new aggregated media items (e.g., by an aggregationcomponent). In one aspect, the new aggregated media item containsportions and/or segments of a plurality of media item of the set ofmedia items. In another aspect, media items are aggregated based on auser(s) input.

FIG. 9 illustrates an example methodology 900 for media item aggregationand display in accordance with an aspect of this disclosure. Initially aplurality of media items are analyzed (e.g., by an analyzer component),synchronized (e.g., by a synchronization component), and ranked (e.g.,by an analyzer component). At 902, an aggregation component, forexample, can aggregate media items with respect to a rank into a newmedia item. In another example, media items can be aggregated withrespect to an associated field of view as compared to other media itemsto generate a new media item.

At 904, a new media item is published (e.g., by an output component).Publishing the new media items can include saving in a computer readablememory or streaming, downloading, broadcasting and/or displaying the newmedia item (e.g., by an output component). For example, displaying mediaitems can be accomplished via electronic devices such as smart phones,tablets, hand held computers, and desktop computers.

At 906, the publishing new media item(s) can be accessed. Accessing thenew memory can include streaming, downloading, and/or displaying the newmedia item. In another aspect, accessing the published new media item(s)can include editing the ranking, aggregation, and analyzing (e.g., usingan editing component).

The systems and processes described below can be embodied withinhardware, such as a single integrated circuit (IC) chip, multiple ICs,an application specific integrated circuit (ASIC), or the like. Further,the order in which some or all of the process blocks appear in eachprocess should not be deemed limiting. Rather, it should be understoodthat some of the process blocks can be executed in a variety of ordersthat are not all of which may be explicitly illustrated herein.

With reference to FIG. 10, a suitable environment 1000 for implementingvarious aspects of the claimed subject matter includes a computer 1002.The computer 1002 includes a processing unit 1004, a system memory 1006,a codec 1005, and a system bus 1008. The system bus 1008 couples systemcomponents including, but not limited to, the system memory 1006 to theprocessing unit 1004. The processing unit 1004 can be any of variousavailable processors. Dual microprocessors and other multiprocessorarchitectures also can be employed as the processing unit 1004.

The system bus 1008 can be any of several types of bus structure(s)including the memory bus or memory controller, a peripheral bus orexternal bus, and/or a local bus using any variety of available busarchitectures including, but not limited to, Industrial StandardArchitecture (ISA), Micro-Channel Architecture (MSA), Extended ISA(EISA), Intelligent Drive Electronics (IDE), VESA Local Bus (VLB),Peripheral Component Interconnect (PCI), Card Bus, Universal Serial Bus(USB), Advanced Graphics Port (AGP), Personal Computer Memory CardInternational Association bus (PCMCIA), Firewire (IEEE 1394), and SmallComputer Systems Interface (SCSI).

The system memory 1006 includes volatile memory 1010 and non-volatilememory 1012. The basic input/output system (BIOS), containing the basicroutines to transfer information between elements within the computer1002, such as during start-up, is stored in non-volatile memory 1012. Byway of illustration, and not limitation, non-volatile memory 1012 caninclude read only memory (ROM), programmable ROM (PROM), electricallyprogrammable ROM (EPROM), electrically erasable programmable ROM(EEPROM), or flash memory. Volatile memory 1010 includes random accessmemory (RAM), which acts as external cache memory. By way ofillustration and not limitation, RAM is available in many forms such asstatic RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), doubledata rate SDRAM (DDR SDRAM), and enhanced SDRAM (ESDRAM).

Computer 1002 may also include removable/non-removable,volatile/non-volatile computer storage media. FIG. 10 illustrates, forexample, a disk storage 1014. Disk storage 1014 includes, but is notlimited to, devices like a magnetic disk drive, solid state disk (SSD)floppy disk drive, tape drive, Zip drive, LS-100 drive, flash memorycard, or memory stick. In addition, disk storage 1014 can includestorage media separately or in combination with other storage mediaincluding, but not limited to, an optical disk drive such as a compactdisk ROM device (CD-ROM), CD recordable drive (CD-R Drive), CDrewritable drive (CD-RW Drive) or a digital versatile disk ROM drive(DVD-ROM). To facilitate connection of the disk storage devices 1014 tothe system bus 1008, a removable or non-removable interface is typicallyused, such as interface 1016.

It is to be appreciated that FIG. 10 describes software, software inexecution, hardware, and/or software in combination with hardware thatacts as an intermediary between users and the basic computer resourcesdescribed in the suitable operating environment 1000. Such softwareincludes an operating system 1018. Operating system 1018, which can bestored on disk storage 1014, acts to control and allocate resources ofthe computer system 1002. Applications 1020 take advantage of themanagement of resources by operating system 1018 through program modules1024, and program data 1026, such as the boot/shutdown transaction tableand the like, stored either in system memory 1006 or on disk storage1014. It is to be appreciated that the claimed subject matter can beimplemented with various operating systems or combinations of operatingsystems. For example, applications 1020 and program data 1026 caninclude software implementing aspects of this disclosure.

A user enters commands or information into the computer 1002 throughinput device(s) 1028. Input devices 1028 include, but are not limitedto, a pointing device such as a mouse, trackball, stylus, touch pad,keyboard, microphone, joystick, game pad, satellite dish, scanner, TVtuner card, digital camera, digital video camera, web camera, and thelike. These and other input devices connect to the processing unit 1004through the system bus 1008 via interface port(s) 1030. Interfaceport(s) 1030 include, for example, a serial port, a parallel port, agame port, and a universal serial bus (USB). Output device(s) 1036 usesome of the same type of ports as input device(s) 1028. Thus, forexample, a USB port may be used to provide input to computer 1002, andto output information from computer 1002 to an output device 1036.Output adapter 1034 is provided to illustrate that there are some outputdevices 1036 like monitors, speakers, and printers, among other outputdevices 1036, which require special adapters. The output adapters 1034include, by way of illustration and not limitation, video and soundcards that provide a means of connection between the output device 1036and the system bus 1008. It should be noted that other devices and/orsystems of devices provide both input and output capabilities such asremote computer(s) 1038.

Computer 1002 can operate in a networked environment using logicalconnections to one or more remote computers, such as remote computer(s)1038. The remote computer(s) 1038 can be a personal computer, a server,a router, a network PC, a workstation, a microprocessor based appliance,a peer device, a smart phone, a tablet, or other network node, andtypically includes many of the elements described relative to computer1002. For purposes of brevity, only a memory storage device 1040 isillustrated with remote computer(s) 1038. Remote computer(s) 1038 islogically connected to computer 1002 through a network interface 1042and then connected via communication connection(s) 1044. Networkinterface 1042 encompasses wire and/or wireless communication networkssuch as local-area networks (LAN), wide-area networks (WAN), andcellular networks. LAN technologies include Fiber Distributed DataInterface (FDDI), Copper Distributed Data Interface (CDDI), Ethernet,Token Ring and the like. WAN technologies include, but are not limitedto, point-to-point links, circuit switching networks like IntegratedServices Digital Networks (ISDN) and variations thereon, packetswitching networks, and Digital Subscriber Lines (DSL).

Communication connection(s) 1044 refers to the hardware/softwareemployed to connect the network interface 1042 to the bus 1008. Whilecommunication connection 1044 is shown for illustrative clarity insidecomputer 1002, it can also be external to computer 1002. Thehardware/software necessary for connection to the network interface 1042includes, for exemplary purposes only, internal and externaltechnologies such as, modems including regular telephone grade modems,cable modems and DSL modems, ISDN adapters, wired and wireless Ethernetcards, hubs, and routers.

Referring now to FIG. 11, there is illustrated a schematic block diagramof a computing environment 1100 in accordance with this specification.The system 1100 includes one or more client(s) 1102, (e.g., computers,smart phones, tablets, cameras, PDA's). The client(s) 1102 can behardware and/or software (e.g., threads, processes, computing devices).The client(s) 1102 can house cookie(s) and/or associated contextualinformation by employing the specification, for example.

The system 1100 also includes one or more server(s) 1104. The server(s)1104 can also be hardware or hardware in combination with software(e.g., threads, processes, computing devices). The servers 1104 canhouse threads to perform transformations by employing aspects of thisdisclosure, for example. One possible communication between a client1102 and a server 1104 can be in the form of a data packet adapted to betransmitted between two or more computer processes wherein data packetsmay include coded media items and/or aggregated media items. The datapacket can include a cookie and/or associated contextual information,for example. The system 1100 includes a communication framework 1106(e.g., a global communication network such as the Internet) that can beemployed to facilitate communications between the client(s) 1102 and theserver(s) 1104.

Communications can be facilitated via a wired (including optical fiber)and/or wireless technology. The client(s) 1102 are operatively connectedto one or more client data store(s) 1108 that can be employed to storeinformation local to the client(s) 1102 (e.g., cookie(s) and/orassociated contextual information). Similarly, the server(s) 1104 areoperatively connected to one or more server data store(s) 1110 that canbe employed to store information local to the servers 1104.

In one implementation, a client 1102 can transfer an encoded file,(e.g., encoded media item), to server 1104. Server 1104 can store thefile, decode the file, or transmit the file to another client 1102. Itis to be appreciated, that a client 1102 can also transfer uncompressedfile to a server 1104 and server 1104 can compress the file inaccordance with the disclosed subject matter. Likewise, server 1104 canencode video information and transmit the information via communicationframework 1106 to one or more clients 1102.

The illustrated aspects of the disclosure may also be practiced indistributed computing environments where certain tasks are performed byremote processing devices that are linked through a communicationsnetwork. In a distributed computing environment, program modules can belocated in both local and remote memory storage devices.

Moreover, it is to be appreciated that various components describedherein can include electrical circuit(s) that can include components andcircuitry elements of suitable value in order to implement theimplementations of this innovation(s). Furthermore, it can beappreciated that many of the various components can be implemented onone or more integrated circuit (IC) chips. For example, in oneimplementation, a set of components can be implemented in a single ICchip. In other implementations, one or more of respective components arefabricated or implemented on separate IC chips.

What has been described above includes examples of the implementationsof the present invention. It is, of course, not possible to describeevery conceivable combination of components or methodologies forpurposes of describing the claimed subject matter, but it is to beappreciated that many further combinations and permutations of thisinnovation are possible. Accordingly, the claimed subject matter isintended to embrace all such alterations, modifications, and variationsthat fall within the spirit and scope of the appended claims. Moreover,the above description of illustrated implementations of this disclosure,including what is described in the Abstract, is not intended to beexhaustive or to limit the disclosed implementations to the preciseforms disclosed. While specific implementations and examples aredescribed herein for illustrative purposes, various modifications arepossible that are considered within the scope of such implementationsand examples, as those skilled in the relevant art can recognize.

In particular and in regard to the various functions performed by theabove described components, devices, circuits, systems and the like, theterms used to describe such components are intended to correspond,unless otherwise indicated, to any component which performs thespecified function of the described component (e.g., a functionalequivalent), even though not structurally equivalent to the disclosedstructure, which performs the function in the herein illustratedexemplary aspects of the claimed subject matter. In this regard, it willalso be recognized that the innovation includes a system as well as acomputer-readable storage medium having computer-executable instructionsfor performing the acts and/or events of the various methods of theclaimed subject matter.

The aforementioned systems/circuits/modules have been described withrespect to interaction between several components/blocks. It can beappreciated that such systems/circuits and components/blocks can includethose components or specified sub-components, some of the specifiedcomponents or sub-components, and/or additional components, andaccording to various permutations and combinations of the foregoing.Sub-components can also be implemented as components communicativelycoupled to other components rather than included within parentcomponents (hierarchical). Additionally, it should be noted that one ormore components may be combined into a single component providingaggregate functionality or divided into several separate sub-components,and any one or more middle layers, such as a management layer, may beprovided to communicatively couple to such sub-components in order toprovide integrated functionality. Any components described herein mayalso interact with one or more other components not specificallydescribed herein but known by those of skill in the art.

Notwithstanding that the numerical ranges and parameters setting forththe broad scope of the invention are approximations, the numericalvalues set forth in the specific examples are reported as precisely aspossible. Any numerical value, however, inherently contains certainerrors necessarily resulting from the standard deviation found in theirrespective testing measurements. Moreover, all ranges disclosed hereinare to be understood to encompass any and all sub-ranges subsumedtherein. For example, a range of “less than or equal to 10” can includeany and all sub-ranges between (and including) the minimum value of zeroand the maximum value of 10, that is, any and all sub-ranges having aminimum value of equal to or greater than zero and a maximum value ofequal to or less than 10, e.g., 1 to 5. In certain cases, the numericalvalues as stated for the parameter can take on negative values.

In addition, while a particular feature of this innovation may have beendisclosed with respect to only one of several implementations, suchfeature may be combined with one or more other features of the otherimplementations as may be desired and advantageous for any given orparticular application. Furthermore, to the extent that the terms“includes,” “including,” “has,” “contains,” variants thereof, and othersimilar words are used in either the detailed description or the claims,these terms are intended to be inclusive in a manner similar to the term“comprising” as an open transition word without precluding anyadditional or other elements.

Reference throughout this specification to “one implementation” or “animplementation” or “one embodiment” or “an embodiment” means that aparticular feature, structure, or characteristic described in connectionwith the implementation is included in at least one implementation or atleast one embodiment. Thus, the appearances of the phrase “in oneimplementation” or “in an implementation” or “in one embodiment” or “inan embodiment” in various places throughout this specification are notnecessarily all referring to the same implementation/embodiment.Furthermore, the particular features, structures, or characteristics maybe combined in any suitable manner in one or moreimplementations/embodiments.

Further, references throughout this specification to an “item,” or“file,” means that a particular structure, feature or object describedin connection with the implementations are not necessarily referring tothe same object. Furthermore, a “file” or “item” can refer to an objectof various formats. While referees to media items generally refer tovideo items (a series of image files with or without audio), it is to beappreciated that media items may be of various formats.

As used in this application, the terms “component,” “module,” “system,”or the like are generally intended to refer to a computer-relatedentity, either hardware (e.g., a circuit), a combination of hardware andsoftware, or an entity related to an operational machine with one ormore specific functionalities. For example, a component may be, but isnot limited to being, a process running on a processor (e.g., digitalsignal processor), a processor, an object, an executable, a thread ofexecution, a program, and/or a computer. By way of illustration, both anapplication running on a controller and the controller can be acomponent. One or more components may reside within a process and/orthread of execution and a component may be localized on one computerand/or distributed between two or more computers. While separatecomponents are depicted in various implementations, it is to beappreciated that the components may be represented in one or more commoncomponent. Further, design of the various implementations can includedifferent component placements, component selections, etc., to achievean optimal performance. Further, a “device” can come in the form ofspecially designed hardware; generalized hardware made specialized bythe execution of software thereon that enables the hardware to performspecific function (e.g., media item aggregation); software stored on acomputer readable medium; or a combination thereof.

Moreover, the words “example” or “exemplary” are used herein to meanserving as an example, instance, or illustration. Any aspect or designdescribed herein as “exemplary” is not necessarily to be construed aspreferred or advantageous over other aspects or designs. Rather, use ofthe words “example” or “exemplary” is intended to present concepts in aconcrete fashion. As used in this application, the term “or” is intendedto mean an inclusive “or” rather than an exclusive “or”. That is, unlessspecified otherwise, or clear from context, “X employs A or B” isintended to mean any of the natural inclusive permutations. That is, ifX employs A; X employs B; or X employs both A and B, then “X employs Aor B” is satisfied under any of the foregoing instances. In addition,the articles “a” and “an” as used in this application and the appendedclaims should generally be construed to mean “one or more” unlessspecified otherwise or clear from context to be directed to a singularform.

What is claimed is:
 1. A media system, comprising: a non-transitorycomputer readable storage medium that stores computer executablecomponents; a hardware processor that executes the following computerexecutable components stored in the non-transitory computer readablestorage medium: an identification component that identifies a set ofmedia items, comprising at least two media items respectively created bydifferent sources that are related to a common event, based at least inpart on determined geographic locations associated with the at least twomedia items; a synchronization component that automatically synchronizesthe set of related media items; an analyzer component that analyzes atleast one metric of respective portions of the set of synchronized mediaitems, individually ranks the portions of the set of media items, groupsthe portions into a set of segments, and determines lengths of thesegment without regard to start times or end times of respective mediaitems, wherein respective segments comprise at least one portion of arespective media item; and an aggregation component that: selects a setof segments of the segments to aggregate; removes a first segment fromthe set of segments based on a threshold segment length; extends alength of a second segment by the length of the first segment, whereinthe second segment is a segment immediately preceding or immediatelyfollowing the first segment; and generates a new media item that is acomposite of the aggregated set of media item segments such that asingle segment of the set of media item segments is associated with asingle segment of the new media item.
 2. The system of claim 1, whereinthe aggregation component selects each segment from the set of segmentsthat are aggregated as a function of the relationship between the users.3. The system of claim 1, wherein the analyzer component identifies arelationship between media items and users of a social network connectedthrough the communication framework based in part on at least one of:email contacts; phone contacts; social network connections; professionalrelationships; membership in a community; or image recognition.
 4. Thesystem of claim 1 further comprising an editing component that receivesuser input regarding at least one of the identification,synchronization, analyzing, dividing, or aggregation.
 5. The system ofclaim 1, wherein the set of segments are aggregated by respectivelystitching the selected segments as a function of the synchronization andthe analysis.
 6. The system of claim 1, wherein the analyzer componentanalyzes the at least one metric based at least one of videocomposition, identified visual pattern, video quality, audio quality, orrelevance.
 7. The system of claim 1, further comprising an outputcomponent that broadcasts, streams, uploads, or transmits the new mediaitem.
 8. The system of claim 1, wherein the analyzer component dividesthe synchronized media items based on a Hidden Markov Model (HMM)Bayesian network and determines the lengths based on the HMM Bayesiannetwork.
 9. A method, comprising: employing a hardware processor toexecute computer executable components stored in a non-transitorycomputer readable storage medium to perform the following acts:receiving a plurality of media items created by a plurality of creators;identifying from the plurality of received media items a set of mediaitems determined to pertain to a common event based at least in part ondetermined geographic locations associated with the set of media items,wherein at least two media items of the set were respectively created bydifferent sources; automatically synchronizing the set of media items atleast as a function of time; analyzing at least one metric of the set ofmedia items; grouping respective frames of the set of synchronized andanalyzed media items into a set of segments, wherein start times or endtimes of the segments are determined without regard for boundaries ofthe plurality of media items; ranking the set of segments as a functionof social connections between respective creators of the set of mediaitems, wherein the social connections are identified through thecommunication framework; selecting a subset of the set of segments foraggregation, based, at least in part, on a threshold segment length;removing a first segment from the subset based on a threshold segmentlength; extends a length of a second segment by the length of the firstsegment, wherein the second segment is a segment immediately precedingor immediately following the first segment; and aggregating the subsetof the set of segments into a new media item; and publishing the newmedia item.
 10. The method of claim 9, wherein: aggregating comprisesstitching the subset of the set of segments into at least one playablemedia item comprising the new media item.
 11. The method of claim 9,wherein the analyzing is performed automatically based at least in parton stored user preferences and the aggregating is performedautomatically based at least in part on stored user preferences.
 12. Themethod of claim 9, further comprising: receiving user input regarding atleast one of the identification, synchronization, analyzing, oraggregation; and the ranking further comprises ranking the at least oneset of segments as a function of the user input.
 13. The method of claim10, wherein the ranking is determined by a Hidden Markov Model (HMM)Bayesian network, wherein the HMM groups the frames or the intervalsinto a segment based on image, video, length, temporal association oraudio qualities.
 14. A non-transitory computer readable storage mediumcomprising computer executable instructions that in response toexecution, cause a computing system to perform operations, comprising:receiving a plurality of media items determined, by identifying commoncharacteristics, including a geographic location, to relate to a commonevent; synchronizing the a plurality of media items at least as afunction of time; analyzing at least one metric of the a plurality ofmedia items; ranking the a plurality of media items, wherein the rankingis based in part on social relationships between users of a socialnetwork, wherein the social relationships are identified through acommunication framework; and grouping the portions into segments;removing a first segment from the subset based on a threshold segmentlength; extending a length of a second segment by the length of thefirst segment, wherein the second segment is a segment immediatelypreceding or immediately following the first segment; and aggregating asubset of the set of segments for aggregated playback, wherein the setof segments are aggregated by stitching segments thereof as a functionof the ranking, such that each of the stitched segments corresponds to adifferent time in the aggregated playback.
 15. The non-transitorycomputer readable storage medium of claim 14 further comprisinginstructions that in response to execution, cause the computing systemto perform the following operation: ranking the set of segments as afunction of user input.
 16. The non-transitory computer readable storagemedium of claim 14, wherein the ranking finds appropriate media itemframes as a function of predefined user relevance.
 17. The system ofclaim 1, wherein the analyzer component divides each media item of theset or media items such that a start of a third segment of the set ofsegments occurs at a time in response to the analyzed at least onemetric of a first media item being determined to have a highest quality,wherein the analyzed at least one metric of the first media item wasdetermined to not have the highest quality during each moment of a timeperiod of a fourth segment, of the set of segments, that immediatelyprecedes the third segment.
 18. The system of claim 17, wherein the oneor more metrics comprise at least one of a determined level of audio, adetected level of motion, or a determined video quality.
 19. The systemof claim 1, wherein the aggregation component further: determineswhether the first segment of the set of segments to be aggregated has alength that is below the threshold segment length.
 20. Thenon-transitory computer readable storage medium of claim 14, wherein thesynchronizing the plurality of media items at least as a function oftime comprises: determining common characteristics of at least two ofthe plurality of media items; and generating a timeline based on thecommon characteristics.